Tcl provides a portable scripting environment for Unix, Windows, and Macintosh that supports string processing and pattern matching, native file system access, shell-like control over other programs, TCP/IP networking, timers, and event-driven I/O. Tcl has traditional programming constructs like variables, loops, procedures, namespaces, error handling, script packages, and dynamic loading of DLLs. Tk provides portable GUIs on UNIX, Windows, and Macintosh. A powerful widget set and the concise scripting interface to Tk make it a breeze to develop sophisticated user interfaces.
X Window Properties Viewer is a simple Motif application that lets you view/edit the X properties that are associated with each X window. A tree viewer lets to see part or all of the windows tree on your X server. After selecting a window you can view all of the resources at once or select individual ones for viewing/editing. Only editing strings is currently supported.
BuildMonkey is an automated build, integration, and test platform for large-scale software development, particularly for distributed teams. It lets you manage multiple projects at once on different platforms and with different build technologies (Ant, make, gmake, etc.) and monitor SCM repositories to know what changed, when, and by whom. Build results are known immediately through email notification, and complete build logs are available via a central build dashboard. BuildMonkey integrates with the BuildMonkey EVT test suite to know the status of your host and network infrastructure at all times. Successful builds can be tagged in the SCM repository so they can be recreated.
curl-loader is a powerful tool for testing and generating load for Web applications. It uses HTTP, FTP, and TLS/SSL stacks. The loader simulates tens and hundreds of thousands of users or clients, each optionally with its own IP address. The goal is to provide an alternative to the Spirent Avalanche and Ixia IxLoad Web application testing solutions.
The Item Response Theory (IRT) library is a set of functions to estimate the items and abilities from the responses of subjects to a questionnaire. The IRT models supported are the logistic model, the nominal response model, the graded response model, and smoothing by penalization and kernel. The project also hosts rirt, a package for the R Project for Statistical Computing, and eirt, an add-in for Excel.